What is R?

R is a programming language and software environment for statistical computing and graphics. Some of its main advantages are:

• free and open source software
• easy sharing of data and code for reproducible research
• collaborative project with many contributors and resources
• extendible with tens of thousands of packages
• state-of-the-art data analysis and visualization tools
• cross-platform software (Windows, Mac Os, UNIX/Linux)

Creators of the R programming language

 

R as standalone program

Graphical user interface (Gui)

Integrated Development Environment (IDE)

What is RStudio?

RStudio is an integrated development environment (IDE) for R and Python.

• developed and maintained by Posit PBC
• free software with optional commercial extensions
• tools for editing, debugging, visualization, and publishing
• workflows for data projects and reproducible research
• cross-platform software (Windows, Mac, Linux)

RStudio panes

What is the console pane?

• The > signals that R is waiting for your input.
• The + signals that R is waiting for you to complete your input.

Press enter to submit your input or escape to cancel it.

R as calculator

The console is ideally suited for quick calculations that are not saved.

1 + 1   # addition

[1] 2

4 - 3   # subtraction

[1] 1

2 * 5   # multiplication

[1] 10

12 / 3  # division

[1] 4

2^2     # exponentiation

[1] 4

sqrt(9) # functions (square root)

[1] 3

pi      # constants

[1] 3.141593

Saving results in objects

Assignments are used in R to store information in objects.

• the operator for assignments is <-

• the notation for an assignment is object <- ...

  a <- 5

• to see the information stored in an object, call it by name

  a

  [1] 5

Naming objects

R is case sensitive, so a and A would refer to different objects.

• objects names can consist of letters (a-z, A-Z), numbers (0-9), and a few special characters like dots (.) and underscores (_)

• if you call an object that does not exist, R will return an error

  A

  Error in eval(expr, envir, enclos): object 'A' not found

• object names cannot start with a number or contain spaces

  1_a <- 5

  Error: <text>:1:2: unexpected input
  1: 1_
       ^

  my a object <- 5

  Error: <text>:1:4: unexpected symbol
  1: my a
         ^

Using objects

• Objects can be used like variables.

  # object "a" is 5, so this is equal to 5 * 2
  a * 2

  [1] 10

• They can be used repeatedly in the same calculation.

  # using "a" multiple times in a calculation
  1 + (a - 2) * a

  [1] 16

• The object’s value does not change when it’s used like that.

  # still the same value
  a

  [1] 5

Changing objects

To change an object, it must be assigned again.

Exercise ✏️

The women’s 100 m world record of 10.49 seconds was set by US athlete Florece Griffith-Joyner in 1988.

1. Store the her finishing time in an object called record.

   Solution

   record <- 10.49

2. Compute her speed in m/s and save it as speed_ms.

   Solution

   speed_ms <- 100 / record

3. Compute her speed in km/h and save it as speed_kmh. (Note that \(km/h = m/s * 3.6\).)

   Solution

   speed_kmh <- speed_ms * 3.6

What is the source pane?

• copy (Ctrl + C) and paste (Ctrl + V) code into the console
• place the cursor on a single line or select code with the mouse and click Run

Comments (#)

# This is comment on a line of its own.
10 - 5 # This is a comment at the end of a line of code.

[1] 5

Exercise ✏️

1. Open a new R script in RStudio.

2. Copy your solution of the last exercise (women’s 100 m world record) into the script.

3. Add comments to explain what each line of code does.

   Solution

   # Save the record in an object called "record".
   record <- 10.49
   
   # Compute the speed in m/s and save it as "speed_ms".
   speed_ms <- 100 / record
   
   # Convert the speed to km/h and save it as "speed_kmh".
   speed_kmh <- speed_ms * 3.6 # Note: km/h = m/s * 3.6

4. Save your script.

5. Run the script and check the results in the console.

What is the environment pane?

Workspace

What is the output pane?

Packages

Packages are collections of R functions, datasets, help menus, and examples that extend the capabilities of Base R.

install.packages("foo")

library(foo)

Use the :: operator (e.g., dplyr::filter()) to be specific about which package a function comes from.

Functions

Objects are one fundamental thing in R. The other fundamental thing are functions. The basic syntax of a function is

function_name(option1, option2, ...).

Functions are used to perform specific tasks. For example, the function mean() computes the mean of a vector of numbers. The result can be assigned to a new object.

# Apply the sqrt() function to the number 9 and assign the result to x.
x <- sqrt(9)
x

[1] 3

Many functions are available in Base R. Additional functions are provided by packages and can be used after loading the package.

Help

# Get help for the function sqrt().
?sqrt

Exercise ✏️

1. Install the package ggplot2 and load it into your current R session.

   Solution

   install.packages("ggplot2")
   library(ggplot2)

2. Get help about the ggsave() function. What does it do?

   Solution

   ?ggsave